{"product_id":"analysis-of-economic-data-isbn-9781118472538","title":"Analysis of Economic Data","description":"\u003cp\u003e\u003ci\u003eAnalysis of Economic Data\u003c\/i\u003e has, over three editions, become firmly established as a successful textbook for students studying data analysis whose primary interest is not in econometrics, statistics or mathematics. \u003c\/p\u003e \u003cp\u003eIt introduces students to basic econometric techniques and shows the reader how to apply these techniques in the context of real-world empirical problems. The book adopts a largely non-mathematical approach relying on verbal and graphical inuition and covers most of the tools used in modern econometrics research.  It contains extensive use of real data examples and involves readers in hands-on computer work.\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e  Preface to the Fourth Edition xi  \u003cp\u003ePreface to the Third Edition xiii\u003c\/p\u003e \u003cp\u003ePreface to the Second Edition xiv\u003c\/p\u003e \u003cp\u003ePreface to the First Edition xv\u003c\/p\u003e \u003cp\u003eChapter 1 Introduction 1\u003c\/p\u003e \u003cp\u003eOrganization of the Book 3\u003c\/p\u003e \u003cp\u003eUseful Background 4\u003c\/p\u003e \u003cp\u003eAppendix 1.1: Mathematical Concepts Used in this Book 4\u003c\/p\u003e \u003cp\u003eEndnote 7\u003c\/p\u003e \u003cp\u003eReferences 7\u003c\/p\u003e \u003cp\u003eChapter 2 Basic Data Handling 8\u003c\/p\u003e \u003cp\u003eTypes of Economic Data 8\u003c\/p\u003e \u003cp\u003eObtaining Data 13\u003c\/p\u003e \u003cp\u003eWorking with Data: Graphical Methods 15\u003c\/p\u003e \u003cp\u003eWorking with Data: Descriptive Statistics 20\u003c\/p\u003e \u003cp\u003eAppendix 2.1: Index Numbers 23\u003c\/p\u003e \u003cp\u003eAppendix 2.2: Advanced Descriptive Statistics 28\u003c\/p\u003e \u003cp\u003eAppendix 2.3: Expected Values and Variances 30\u003c\/p\u003e \u003cp\u003eEndnotes 32\u003c\/p\u003e \u003cp\u003eChapter 3 Correlation 34\u003c\/p\u003e \u003cp\u003eUnderstanding Correlation 34\u003c\/p\u003e \u003cp\u003eUnderstanding Why Variables Are Correlated 38\u003c\/p\u003e \u003cp\u003eUnderstanding Correlation Through XY-Plots 41\u003c\/p\u003e \u003cp\u003eCorrelation Between Several Variables 45\u003c\/p\u003e \u003cp\u003eAppendix 3.1: Mathematical Details 46\u003c\/p\u003e \u003cp\u003eEndnotes 46\u003c\/p\u003e \u003cp\u003eChapter 4 Introduction to Simple Regression 48\u003c\/p\u003e \u003cp\u003eRegression as a Best Fitting Line 48\u003c\/p\u003e \u003cp\u003eInterpreting OLS Estimates 53\u003c\/p\u003e \u003cp\u003eFitted Values and R2: Measuring the Fit of a Regression Model 56\u003c\/p\u003e \u003cp\u003eNonlinearity in Regression 60\u003c\/p\u003e \u003cp\u003eAppendix 4.1: Mathematical Details 64\u003c\/p\u003e \u003cp\u003eEndnotes 66\u003c\/p\u003e \u003cp\u003eChapter 5 Statistical Aspects of Regression 67\u003c\/p\u003e \u003cp\u003eWhich Factors Affect the Accuracy of the Estimate βˆ ? 68\u003c\/p\u003e \u003cp\u003eCalculating a Confidence Interval for β 72\u003c\/p\u003e \u003cp\u003eTesting whether β = 0 78\u003c\/p\u003e \u003cp\u003eHypothesis Testing Involving R2: The F-Statistic 82\u003c\/p\u003e \u003cp\u003eAppendix 5.1: Using Statistical Tables to Test Whether β = 0 85\u003c\/p\u003e \u003cp\u003eEndnotes 87\u003c\/p\u003e \u003cp\u003eReferences 88\u003c\/p\u003e \u003cp\u003eChapter 6 Multiple Regression 89\u003c\/p\u003e \u003cp\u003eRegression as a Best Fitting Line 91\u003c\/p\u003e \u003cp\u003eOLS Estimation of the Multiple Regression Model 91\u003c\/p\u003e \u003cp\u003eStatistical Aspects of Multiple Regression 91\u003c\/p\u003e \u003cp\u003eInterpreting OLS Estimates 92\u003c\/p\u003e \u003cp\u003ePitfalls of Using Simple Regression in a Multiple Regression Context 95\u003c\/p\u003e \u003cp\u003eOmitted Variables Bias 97\u003c\/p\u003e \u003cp\u003eMulticollinearity 99\u003c\/p\u003e \u003cp\u003eAppendix 6.1: Mathematical Interpretation of Regression Coefficients 105\u003c\/p\u003e \u003cp\u003eEndnotes 105\u003c\/p\u003e \u003cp\u003eChapter 7 Regression with Dummy Variables 107\u003c\/p\u003e \u003cp\u003eSimple Regression with a Dummy Variable 109\u003c\/p\u003e \u003cp\u003eMultiple Regression with Dummy Variables 110\u003c\/p\u003e \u003cp\u003eMultiple Regression with Dummy and Non-dummy Explanatory Variables 113\u003c\/p\u003e \u003cp\u003eInteracting Dummy and Non-dummy Variables 116\u003c\/p\u003e \u003cp\u003eChapter 8 Qualitative Choice Models 119\u003c\/p\u003e \u003cp\u003eThe Economics of Choice 120\u003c\/p\u003e \u003cp\u003eChoice Probabilities and the Logit and Probit Models 121\u003c\/p\u003e \u003cp\u003eAppendix 8.1: Choice Probabilities in the Logit Model 128\u003c\/p\u003e \u003cp\u003eReferences 130\u003c\/p\u003e \u003cp\u003eChapter 9 Regression with Time Lags: Distributed Lag Models 131\u003c\/p\u003e \u003cp\u003eLagged Variables 133\u003c\/p\u003e \u003cp\u003eNotation 135\u003c\/p\u003e \u003cp\u003eSelection of Lag Order 138\u003c\/p\u003e \u003cp\u003eAppendix 9.1: Other Distributed Lag Models 141\u003c\/p\u003e \u003cp\u003eEndnotes 143\u003c\/p\u003e \u003cp\u003eChapter 10 Univariate Time Series Analysis 144\u003c\/p\u003e \u003cp\u003eThe Autocorrelation Function 147\u003c\/p\u003e \u003cp\u003eThe Autoregressive Model for Univariate Time Series 151\u003c\/p\u003e \u003cp\u003eNonstationary versus Stationary Time Series 154\u003c\/p\u003e \u003cp\u003eExtensions of the AR(1) Model 156\u003c\/p\u003e \u003cp\u003eTesting in the AR(p) with Deterministic Trend Model 161\u003c\/p\u003e \u003cp\u003eAppendix 10.1: Mathematical Intuition for the AR(1) Model 166\u003c\/p\u003e \u003cp\u003eEndnotes 167\u003c\/p\u003e \u003cp\u003eReferences 168\u003c\/p\u003e \u003cp\u003eChapter 11 Regression with Time Series Variables 169\u003c\/p\u003e \u003cp\u003eTime Series Regression when X and Y Are Stationary 170\u003c\/p\u003e \u003cp\u003eTime Series Regression when Y and X Have Unit Roots: Spurious Regression 174\u003c\/p\u003e \u003cp\u003eTime Series Regression when Y and X Have Unit Roots: Cointegration 174\u003c\/p\u003e \u003cp\u003eEstimation and Testing with Cointegrated Variables 177\u003c\/p\u003e \u003cp\u003eTime Series Regression when Y and X Are Cointegrated: The Error Correction Model 181\u003c\/p\u003e \u003cp\u003eTime Series Regression when Y and X Have Unit Roots but Are Not Cointegrated 184\u003c\/p\u003e \u003cp\u003eEndnotes 187\u003c\/p\u003e \u003cp\u003eChapter 12 Applications of Time Series Methods in Macroeconomics and Finance 189\u003c\/p\u003e \u003cp\u003eFinancial Volatility 190\u003c\/p\u003e \u003cp\u003eAutoregressive Conditional Heteroskedasticity (ARCH) 196\u003c\/p\u003e \u003cp\u003eGranger Causality 200\u003c\/p\u003e \u003cp\u003eVector Autoregressions 206\u003c\/p\u003e \u003cp\u003eAppendix 12.1: Hypothesis Tests Involving More than One Coefficient 221\u003c\/p\u003e \u003cp\u003eEndnotes 225\u003c\/p\u003e \u003cp\u003eReference 226\u003c\/p\u003e \u003cp\u003eChapter 13 Limitations and Extensions 227\u003c\/p\u003e \u003cp\u003eProblems that Occur when the Dependent Variable Has Particular Forms 228\u003cbr\u003e \u003cbr\u003e Problems that Occur when the Errors Have Particular Forms 229\u003c\/p\u003e \u003cp\u003eProblems that Call for the Use of Multiple Equation Models 231\u003c\/p\u003e \u003cp\u003eEndnotes 236\u003c\/p\u003e \u003cp\u003eAppendix A Writing an Empirical Project 237\u003c\/p\u003e \u003cp\u003eDescription of a Typical Empirical Project 237\u003c\/p\u003e \u003cp\u003eGeneral Considerations 239\u003c\/p\u003e \u003cp\u003eProject Topics 240\u003c\/p\u003e \u003cp\u003eReferences 244\u003c\/p\u003e \u003cp\u003eAppendix B Data Directory 246\u003c\/p\u003e \u003cp\u003eAuthor Index 249\u003c\/p\u003e \u003cp\u003eSubject Index 250\u003c\/p\u003e  \u003cp\u003e\u003cstrong\u003eGary Koop\u003c\/strong\u003e is Professor of Economics at the University of Strathclyde. He previously held professorial positions at the Universities of Toronto, Edinburgh, Glasgow and Leicester. He has also held academic posts at the University of Cambridge, the London School of Economics, Boston University and Queen's University, Canada. Gary is the associate editor of the \u003cem\u003eJournal of Econometrics\u003c\/em\u003e, \u003cem\u003eEconometrics Reviews\u003c\/em\u003e, the \u003cem\u003eJournal of Empirical Finance\u003c\/em\u003e, Studies in Nonlinear Dynamics and Econometrics and the \u003cem\u003eJournal of Applied Econometrics\u003c\/em\u003e. He is the author of: \u003cem\u003eIntroduction to Econometrics, Bayesian Econometrics\u003c\/em\u003e and \u003cem\u003eAnalysis of Financial Data\u003c\/em\u003e, all of which are published by Wiley.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988733903077,"sku":"NP9781118472538","price":65.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118472538.jpg?v=1761781378","url":"https:\/\/k12savings.com\/es\/products\/analysis-of-economic-data-isbn-9781118472538","provider":"K12savings","version":"1.0","type":"link"}